Senior Enterprise Tech Support Engineer - Incident & Debugging

ABOUT YOU SE & Co. KG; New York (NY); On-site; USD 110,000 - 160,000; Full time

Benefits offered by this job

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Job summary

SCAYLE is seeking an experienced enterprise support engineer to investigate complex B2B SaaS issues, using Datadog and logs to diagnose distributed systems. You will read code, query SQL, and manage tickets through a full lifecycle while communicating clearly with major customers.

You will own a technical domain, develop playbooks, and contribute to knowledge bases. The role includes on-call coverage and collaboration with engineering to drive systemic improvements.

Qualifications

• 5+ years of hands-on technical support or systems engineering in a complex B2B SaaS or enterprise environment.
• Proven experience supporting enterprise customers, ideally in a SaaS or cloud-based product environment.
• Experience improving how a support team works: documentation, playbooks, processes, quality standards.
• Experience supporting or mentoring less experienced colleagues.
• Comfortable reading server-side code in at least one language to trace logic and verify code paths.
• Hands-on experience with observability and central logging tooling - Datadog preferred; familiarity with central logging platforms (Kibana / OpenSearch / Elasticsearch) is a strong plus.
• Comfortable searching logs, reading distributed traces, querying metrics.
• Solid SQL skills - able to query relational databases to verify system state, reproduce issues, and understand data models.
• Working knowledge of distributed systems concepts - async vs. synchronous communication, queues, retries, idempotency, eventual consistency.
• Comfort with HTTP and API debugging - curl, response headers, status codes, basic DNS, REST and webhook flows.
• Familiarity with cloud-based, multi-tenant SaaS architectures - understanding tenant isolation and configuration delivery is a strong advantage.
• Hands-on with AI tooling - you already use AI in your daily work and have gone beyond typing into a chat window: built an agent, automated a workflow, written something against an API, or experimented seriously in your own time.

Responsibilities

• Investigate technical issues reported by enterprise customers - analyse symptoms, form hypotheses, follow the evidence to the root cause
• Use observability tooling to diagnose issues across distributed services
• Read code across multiple repositories to verify hypotheses and trace request flows
• Query databases when needed to confirm system state and reproduce issues
• Manage tickets through their full lifecycle, from intake to resolution, across the support → engineering escalation chain
• Communicate proactively and professionally with enterprise customers: structured updates, clear next steps, calibrated expectation management
• Partner with engineering teams when escalation is needed - frame issues clearly, provide reproducible evidence, advocate for customer impact
• Document findings, contribute to internal knowledge bases, and surface recurring patterns to drive systemic improvements
• Participate in rotational on-call coverage for high‑severity incidents (evenings, weekends), supporting our enterprise customers when issues cannot wait until business hours
• Take ownership of a technical domain within the platform and act as the reference point for the team in that area
• Develop and maintain investigation playbooks, runbooks, escalation paths, and knowledge base content the team relies on
• Analyse recurring failure patterns to drive platform improvements, and advocate for customer‑impacting fixes by framing systemic risk and business impact to product and platform teams
• Apply AI tooling to our daily work - evaluate tools and agents, identify where they add leverage, and share what works with the team
• Support the onboarding of new team members and help raise the standard for technical investigation and customer communication

Skills

Enterprise customer support

Documentation

Mentoring

Code reading

Distributed systems concepts

API debugging

Cloud architecture

AI tooling

Tools

Datadog

Kibana/OpenSearch/Elasticsearch

Job description

SCAYLE is seeking an experienced enterprise support engineer to investigate complex B2B SaaS issues, using Datadog and logs to diagnose distributed systems. You will read code, query SQL, and manage tickets through a full lifecycle while communicating clearly with major customers.

You will own a technical domain, develop playbooks, and contribute to knowledge bases. The role includes on-call coverage and collaboration with engineering to drive systemic improvements.